Objective: To evaluate the 3 alcohol consumption questions from the Alcohol Use Disorders Identification Test (AUDIT-C) as a brief screening test for heavy drinking and/or active alcohol abuse or dependence. Methods:Patients from 3 Veterans Affairs general medical clinics were mailed questionnaires. A random, weighted sample of Health History Questionnaire respondents, who had 5 or more drinks over the past year, were eligible for telephone interviews (N = 447). Heavy drinkers were oversampled 2:1. Patients were excluded if they could not be contacted by telephone, were too ill for interviews, or were female (n = 54). Areas under receiver operating characteristic curves (AUROCs) were used to compare mailed alcohol screening questionnaires (AUDIT-C and full AUDIT) with 3 comparison standards based on telephone interviews: (1) past year heavy drinking (Ͼ14 drinks/week or Ն5 drinks/ occasion); (2) active alcohol abuse or dependence according to the Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition, criteria;and (3) either.Results: Of 393 eligible patients, 243 (62%) completed AUDIT-C and interviews. For detecting heavy drinking, AUDIT-C had a higher AUROC than the full AUDIT (0.891 vs 0.881; P = .03). Although the full AUDIT performed better than AUDIT-C for detecting active alcohol abuse or dependence (0.811 vs 0.786; P<.001), the 2 questionnaires performed similarly for detecting heavy drinking and/or active abuse or dependence (0.880 vs 0.881).Conclusions: Three questions about alcohol consumption (AUDIT-C) appear to be a practical, valid primary care screening test for heavy drinking and/or active alcohol abuse or dependence.

The incidence of warfarin-associated bleeding may be reduced by attending to modifiable risk factors (that is, highly variable PTRs and values greater than 2.0), frequent monitoring early in treatment, and careful patient selection. Older age, in and of itself, is not a risk factor.

Objective. We compared single-and multi-item measures of general self-rated health (GSRH) to predict mortality and clinical events a large population of veteran patients. Data Source/Study Setting. We analyzed prospective cohort data collected from 21,732 patients as part of the Veterans Affairs Ambulatory Care Quality Improvement Project (ACQUIP), a randomized controlled trial investigating quality-of-care interventions. Study Design. We created an age-adjusted, logistic regression model for each predictor and outcome combination, and estimated the odds of events by response category of the GSRH question and compared the discriminative ability of the predictors by developing receiver operator characteristic curves and comparing the associated area under the curve (AUC)/c-statistic for the single-and multi-item measures. Data Collection/Extraction Methods. All patients were sent a baseline assessment that included a multi-item measure of general health, the 36-item Medical Outcomes Study Short Form (SF-36), and an inventory of comorbid conditions. We compared the predictive and discriminative ability of the GSRH to the SF-36 physical component score (PCS), the mental component score (MCS), and the Seattle index of comorbidity (SIC). The GSRH is an item included in the SF-36, with the wording: ''In general, would you say your health is: Excellent, Very Good, Good, Fair, Poor?'' Principal Findings. The GSRH, PCS, and SIC had comparable AUC for predicting mortality (AUC 0.74, 0.73, and 0.73, respectively); hospitalization (AUC 0.63, 0.64, and 0.60, respectively); and high outpatient use (AUC 0.61, 0.61, and 0.60, respectively). The MCS had statistically poorer discriminatory performance for mortality and hospitalization than any other other predictors ( po.001). Conclusions. The GSRH response categories can be used to stratify patients with varying risks for adverse outcomes. Patients reporting ''poor'' health are at significantly greater odds of dying or requiring health care resources compared with their peers. The GSRH, collectable at the point of care, is comparable with longer instruments.

Background — Although patient-reported health status measures have been used as end points in clinical trials, they are rarely used in other settings. Demonstrating that they independently predict mortality and hospitalizations among outpatients with coronary disease could emphasize their clinical value. Methods and Results — This study evaluated the prognostic utility of the Seattle Angina Questionnaire (SAQ), a disease-specific health status measure for patients with coronary artery disease. Patients were enrolled in a prospective cohort study from 6 Veterans Affairs General Internal Medicine Clinics. All patients reporting coronary artery disease who completed a SAQ and had 1 year of follow-up were analyzed (n=5558). SAQ predictor variables were the physical limitation, angina stability, angina frequency, and quality-of-life scores. The primary outcome was 1-year all-cause mortality, and a secondary outcome was hospitalization for acute coronary syndrome (ACS). Lower SAQ scores were associated with increased risks of mortality and ACS admissions. Prognostic models controlling for demographic and clinical characteristics demonstrated significant independent mortality risk with lower SAQ physical limitation scores; odds ratios for mild, moderate, and severe limitation were 1.5, 2.0, and 4.0 versus minimal limitation ( P <0.001). Odds ratios for mild, moderate, and severe angina frequency were 0.8, 1.2, and 1.6 ( P =0.078). The odds ratios for ACS admission among those with mild, moderate, and severe angina frequency were 1.4, 2.0, and 2.2, respectively ( P =0.016). Conclusions — SAQ scores are independently associated with 1-year mortality and ACS among outpatients with coronary disease and may serve a valuable role in the risk stratification of such patients.